w2v2-base-pretrained_lr5e-5_at0.8_da0.5 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr5e-5_at0.8_da0.5

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr5e-5_at0.8_da0.5

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.3736
Wer: 0.1858

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
20.81	10.87	250	3.8675	1.0
3.2992	21.74	500	3.1858	1.0
3.0813	32.61	750	3.0758	1.0
2.3718	43.48	1000	1.3480	0.8266
0.3075	54.35	1250	1.6498	0.2290
0.1081	65.22	1500	1.8213	0.2012
0.0732	76.09	1750	1.8933	0.1952
0.0517	86.96	2000	2.0154	0.2059
0.0386	97.83	2250	2.0444	0.1948
0.0323	108.7	2500	2.2603	0.2003
0.0272	119.57	2750	2.2578	0.1952
0.0234	130.43	3000	2.2854	0.1880
0.0203	141.3	3250	2.3553	0.1867
0.0181	152.17	3500	2.3723	0.1905
0.0165	163.04	3750	2.3793	0.1854
0.016	173.91	4000	2.3736	0.1858

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1